How a layered rem architecture brings cognition to today's mobile networks

Abstract

In this article, we present a layered radio environment map architecture along with its applications to the self-organizing network functionalities of heterogeneous LTE radio access networks comprising macrocells and femtocells. In this architecture, the functional blocks reappear with different spatial and temporal granularity at different architectural layers. Although the radio environment map is one of the key promising technologies to enable future cognitive radio networks, it can be already applied to provide limited cognitive capabilities to today's commercial networks too. We explain why, and show how, this architecture can support today’s LTE self-organizing network functions like automatic neighbor relation and minimization of drive tests, and also allow the smooth introduction of new radio access technologies through refarming. We also demonstrate some of the quantitative benefits adopting radio environment map technologies can bring using the minimization of drive tests as an example.